Stochastic Environmental modeling for Nuclear Waste Management
Loading...
Date
2017-10-03
Authors
Madhusoothanan, Vimala Madhangi
Journal Title
Journal ISSN
Volume Title
Publisher
University of Waterloo
Abstract
Deep geological repositories are identified as possible disposal site for safely isolating highly radioactive nuclear waste from affecting humans and the environment. These repositories are multi barrier systems and safety of the system is very crucial since failure of the system will lead to radioactive contamination, which is harmful to the environment.
It is necessary to model the possible failure of the system, one of the most significant parameter is the mass transfer between the barriers in the multiple barrier system given by equivalent flow rates, half time of the solute and the delay time between the inflow and outflow of the barriers. The entire model is constructed based on the conservation assumption of mass flux. The model is used to analyze radioactive decays of the two long lived radioactive species C-14 (neutral non-sorbing nuclide) and I-129 (anionic non-sorbing nuclide). From the radioactive decay of these radionuclides the equivalent exposure is calculated to ensure that it is well below the current safety limits specified by the Regulator.
The geosphere and bentonite buffer, which are a part of the multi barrier system, are porous media and modeling the seepage is done using Darcy’s law. Modeling seepage of water is important because water acts as a carrier for several elements that can potentially corrode the copper coating. The copper coating is an integral part of the multi barrier system, and an essential element of of the used fuel container.
This thesis analyzes effects of a wide spectrum of uncertainties on the performance of the analytical solution obtained from the deterministic model is used to (i) consider parameter uncertainties, and (ii) derive stochastic solution of governing equations for the following two cases: (1) water seepage into the DGR, and (2) Mass outflow of radioactive material. Case I a man-made system whose uncertain and time invariant parameters, whereas Case II considers stochastic nature of the natural environment. Conclusions from this study support a high level of safety aspects of DGR for the disposal of high level radioactive waste.
Description
Keywords
Nuclear waste disposal, Environmental modeling, Stochastic modeling, Deep geological repository